Resumen:En el presente artículo se simula el SIEFOREs,el invertir su componente de renta variable socialmente responsables, mismas sustentable (IPCS). Para lograr CONSAR y se recalculó el IPCS a enero de 2004 con el método de capita índice como insumo, se simuló el es emplear el IPCS, el IPCcomp y el IPC maximiza el índice de Sharpe acciones en el IPCS,las SIEFOREs no pierden desempeño logrado ya seacon que si una SIEFORE utilizara el IPCS durante periodos de alta volatilidad emplear los otros dos índices Clasificación JEL: C580, G11, G170, G23. Palabras clave: ModelosMarkovianos de cambio de régimen, Diversi portafolios, Simulación y pronóstico The benefits of Socially Responsible Investment in the performance of Mexican Abstract:In the present paper we simulate the impact of investing in socially responsible stocks (members of the IPC sustainable index or IPCS) in Mexican pension funds or SIEFOREs. In order to do this, we used the authorized investment policy by CONSAR and we recalculated the IPCS index from January 2004 by using the market cap method. With this recalculated index we simulated the performance of three SIEFOREs that invest their Mexican equity proceedings either in the IPCS, the IPCcomp or the IPC index. Our results show a sound mean-variance efficiency if the SIEFOREs invest in the IPCS index only. We se simula el impacto que tiene,en la política de su componente de renta variable nacional en acciones socialmente responsables, mismas que formen parte del índice de precios y cotizaciones sustentable (IPCS). Para lograr esto, se empleó la política de inversión autorizada por la CONSAR y se recalculó el IPCS a enero de 2004 con el método de capita se simuló el comportamiento de tres SIEFOREs cuya única diferencia IPCcomp y el IPC en un portafolio de mínima varianza y otro que maximiza el índice de Sharpe. Los resultados observan que, al invertir las SIEFOREs no pierden eficiencia media-varianza, respecto al con el IPC o elIPCcomp.De manera complementaria se aprecia que si una SIEFORE utilizara el IPCS en un portafolio que maximice el índice de Sharpe periodos de alta volatilidad, el desempeño del mismoes mayor dos índices.n JEL: C580, G11, G170, G23. losMarkovianos de cambio de régimen, Diversificación, Sel n y pronósticofinanciero, Inversiónsocialmenteresponsable. The benefits of Socially Responsible Investment in the performance of Mexican pension funds.we simulate the impact of investing in socially responsible stocks (members of the IPC sustainable index or IPCS) in Mexican pension funds or SIEFOREs. In order to do this, we used the authorized investment policy by CONSAR and we dex from January 2004 by using the market cap method. With this recalculated index we simulated the performance of three SIEFOREs that invest their Mexican equity proceedings either in the IPCS, the IPCcomp or the IPC index. Our results ariance efficiency if the SIEFOREs invest in the IPCS index only. We a y Ciencias Administrativas, Universidad Michoacana de San e Hidalgo Ave. Francisco J. Mújica S/N Edificio AII Col...
In this paper, we test the use of Markov-switching (MS) GARCH (MSGARCH) models for trading either oil or natural gas futures. Using weekly data from 7 January 1994 to 31 May 2019, we tested the next trading rule: to invest in the simulated commodity if the investor expects to be in the low-volatility regime at t + 1 or to otherwise hold the risk-free asset. Assumptions for our simulations included the following: (1) we assumed that the investors trade in a homogeneous (Gaussian or t-Student) two regime context and (2) the investor used a time-fixed, ARCH, or GARCH variance in each regime. Our results suggest that the use of the MS Gaussian model, with time-fixed variance, leads to the best performance in the oil market. For the case of natural gas, we found no benefit of using our trading rule against a buy-and-hold strategy in the three-month U.S. Treasury bills.
In the present paper, we test the benefit of using Markov-Switching models and volatility futures diversification in a Euro-based stock portfolio. With weekly data of the Eurostoxx 50 (ESTOXX50) stock index, we forecasted the smoothed regime-specific probabilities at T + 1 and used them as the weighting method of a diversified portfolio in ESTOXX50 and ESTOSS50 volatility index (VSTOXX) futures. With the estimated smoothed probabilities from 9 July 2009 to 29 September 2020, we simulated the performance of three theoretical investors who paid different trading costs and invested in ESTOXX50 during calm periods (low volatility regime) or VSTOXX futures and the three-month German treasury bills in distressed or highly distressed periods (high and extreme volatility regimes). Our results suggest that diversification benefits hold in the short-term, but if a given investor manages a two-asset portfolio with ESTOXX50 and our simulated portfolios, the stock portfolio’s performance is enhanced significantly, in the long term, with the presence of trading costs. These results are of use to practitioners for algorithmic and active trading applications in ESTOXX50 ETFs and VSTOXX futures.
In the present paper we tested the use of Markov-switching Generalized AutoRegressive Conditional Heteroscedasticity (MS-GARCH) models and their not generalized (MS-ARCH) version. This, for active trading decisions in the coffee, cocoa, and sugar future markets. With weekly data from 7 January 2000 to 3 April 2020, we simulated the performance that a futures’ trader would have had, had she used the next trading algorithm: To invest in the security if the probability of being in a distress regime is less or equal to 50% or to invest in the U.S. three-month Treasury bill otherwise. Our results suggest that the use of t-student Markov Switching Component ARCH Model (MS-ARCH) models is appropriate for active trading in the cocoa futures and the Gaussian MS-GARCH is appropriate for sugar. For the specific case of the coffee market, we did not find evidence in favor of the use of MS-GARCH models. This is so by the fact that the trading algorithm led to inaccurate trading signs. Our results are of potential use for futures’ position traders or portfolio managers who want a quantitative trading algorithm for active trading in these commodity futures.
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